{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import torchvision\n",
    "import torchvision.transforms as transforms\n",
    "from torch.optim import lr_scheduler\n",
    "import numpy as np\n",
    "import time\n",
    "import copy\n",
    "import os\n",
    "from tools import *\n",
    "\n",
    "\n",
    "\n",
    "# 定义基本模块\n",
    "class BasicBlock(nn.Module):\n",
    "    expansion = 1\n",
    "\n",
    "    def __init__(self, in_planes, planes, stride=1):\n",
    "        super(BasicBlock, self).__init__()\n",
    "        self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)\n",
    "        self.bn1 = nn.BatchNorm2d(planes)\n",
    "        self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=1, padding=1, bias=False)\n",
    "        self.bn2 = nn.BatchNorm2d(planes)\n",
    "\n",
    "        self.shortcut = nn.Sequential()\n",
    "        if stride != 1 or in_planes != self.expansion * planes:\n",
    "            self.shortcut = nn.Sequential(\n",
    "                nn.Conv2d(in_planes, self.expansion * planes, kernel_size=1, stride=stride, bias=False),\n",
    "                nn.BatchNorm2d(self.expansion * planes)\n",
    "            )\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        out = self.bn2(self.conv2(out))\n",
    "        out += self.shortcut(x)\n",
    "        out = F.relu(out)\n",
    "        return out\n",
    "\n",
    "# 定义 ResNet\n",
    "class ResNet(nn.Module):\n",
    "    def __init__(self, block, num_blocks, num_classes=100):\n",
    "        super(ResNet, self).__init__()\n",
    "        self.in_planes = 64\n",
    "\n",
    "        self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=1, padding=1, bias=False)\n",
    "        self.bn1 = nn.BatchNorm2d(64)\n",
    "        self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)\n",
    "        self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)\n",
    "        self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)\n",
    "        self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)\n",
    "        self.linear = nn.Linear(512 * block.expansion, num_classes)\n",
    "\n",
    "    def _make_layer(self, block, planes, num_blocks, stride):\n",
    "        strides = [stride] + [1] * (num_blocks - 1)\n",
    "        layers = []\n",
    "        for stride in strides:\n",
    "            layers.append(block(self.in_planes, planes, stride))\n",
    "            self.in_planes = planes * block.expansion\n",
    "        return nn.Sequential(*layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        out = F.relu(self.bn1(self.conv1(x)))\n",
    "        out = self.layer1(out)\n",
    "        out = self.layer2(out)\n",
    "        out = self.layer3(out)\n",
    "        out = self.layer4(out)\n",
    "        out = F.avg_pool2d(out, 4)\n",
    "        out = out.view(out.size(0), -1)\n",
    "        out = self.linear(out)\n",
    "        return out\n",
    "\n",
    "# 定义 ResNet-18\n",
    "def ResNet18():\n",
    "    return ResNet(BasicBlock, [2, 2, 2, 2])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n",
      "Files already downloaded and verified\n",
      "cuda:0\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "# 数据预处理\n",
    "transform_train = transforms.Compose([\n",
    "    transforms.RandomHorizontalFlip(),\n",
    "    transforms.RandomCrop(32, padding=4),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize((0.5071, 0.4865, 0.4409), (0.2673, 0.2564, 0.2762)),\n",
    "])\n",
    "\n",
    "transform_test = transforms.Compose([\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize((0.5071, 0.4865, 0.4409), (0.2673, 0.2564, 0.2762)),\n",
    "])\n",
    "\n",
    "# 加载数据集\n",
    "trainset = torchvision.datasets.CIFAR100(root='./data', train=True, download=True, transform=transform_train)\n",
    "trainloader = torch.utils.data.DataLoader(trainset, batch_size=128, shuffle=True, num_workers=2)\n",
    "\n",
    "testset = torchvision.datasets.CIFAR100(root='./data', train=False, download=True, transform=transform_test)\n",
    "testloader = torch.utils.data.DataLoader(testset, batch_size=100, shuffle=False, num_workers=2)\n",
    "\n",
    "# 实例化模型\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "print(device)\n",
    "model = ResNet18().to(device)\n",
    "\n",
    "# 定义损失函数和优化器\n",
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = optim.SGD(model.parameters(), lr=0.01, momentum=0.9, weight_decay=5e-4)\n",
    "scheduler = lr_scheduler.StepLR(optimizer, step_size=50, gamma=0.1)\n",
    "\n",
    "epochs=25\n",
    "model_name='resnet18'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #一些参数的设置\n",
    "# device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "# learning_rate=0.01\n",
    "# momentum=0.9\n",
    "# weight_decay=0.0001\n",
    "# batch_size=128\n",
    "# epochs=25\n",
    "# data_path='./data'\n",
    "# model_name='ResNet18'+'epoch='+str(epochs)\n",
    "# print(device)\n",
    "# model=ResNet18().to(device)\n",
    "# criterion=nn.CrossEntropyLoss()\n",
    "# optimizer = optim.SGD(model.parameters(), lr=learning_rate, momentum=momentum, weight_decay=weight_decay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #数据集的加载\n",
    "# trainloader,testloader=get_data_loaders(batch_size=batch_size,num_workers=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch:0,train_loss:3.6842,train_acc:13.3940,train_top5_acc:36.4280,test_loss:3.4064,test_acc:17.8500,test_top5_acc:46.4500\n",
      "epoch:1,train_loss:2.8523,train_acc:27.6460,train_top5_acc:58.9120,test_loss:2.6676,test_acc:31.9800,test_top5_acc:64.3200\n",
      "epoch:2,train_loss:2.3182,train_acc:38.4920,train_top5_acc:71.3800,test_loss:2.3703,test_acc:38.1500,test_top5_acc:70.4700\n",
      "epoch:3,train_loss:1.9990,train_acc:45.5760,train_top5_acc:77.8100,test_loss:2.0752,test_acc:44.0000,test_top5_acc:76.3700\n",
      "epoch:4,train_loss:1.7710,train_acc:50.9200,train_top5_acc:81.8600,test_loss:2.0098,test_acc:46.7100,test_top5_acc:78.2900\n",
      "epoch:5,train_loss:1.5944,train_acc:55.0740,train_top5_acc:84.9120,test_loss:1.8006,test_acc:51.8600,test_top5_acc:80.8200\n",
      "epoch:6,train_loss:1.4591,train_acc:58.3620,train_top5_acc:87.1360,test_loss:1.6976,test_acc:53.7200,test_top5_acc:83.0300\n",
      "epoch:7,train_loss:1.3433,train_acc:61.0080,train_top5_acc:88.8880,test_loss:1.6282,test_acc:55.6200,test_top5_acc:84.0600\n",
      "epoch:8,train_loss:1.2427,train_acc:64.0720,train_top5_acc:90.2220,test_loss:1.7111,test_acc:54.5100,test_top5_acc:83.5000\n",
      "epoch:9,train_loss:1.1614,train_acc:66.0580,train_top5_acc:91.3260,test_loss:1.4600,test_acc:60.1300,test_top5_acc:86.5600\n",
      "epoch:10,train_loss:1.0847,train_acc:68.1900,train_top5_acc:92.3720,test_loss:1.5152,test_acc:58.0300,test_top5_acc:87.0200\n",
      "epoch:11,train_loss:1.0117,train_acc:69.7980,train_top5_acc:93.4620,test_loss:1.4498,test_acc:61.1400,test_top5_acc:86.8600\n",
      "epoch:12,train_loss:0.9489,train_acc:71.6680,train_top5_acc:94.1260,test_loss:1.3876,test_acc:61.6200,test_top5_acc:88.3600\n",
      "epoch:13,train_loss:0.8901,train_acc:73.2700,train_top5_acc:94.6600,test_loss:1.4178,test_acc:61.3900,test_top5_acc:88.0600\n",
      "epoch:14,train_loss:0.8396,train_acc:74.7940,train_top5_acc:95.2660,test_loss:1.3763,test_acc:63.2100,test_top5_acc:88.4700\n",
      "epoch:15,train_loss:0.7833,train_acc:76.4060,train_top5_acc:95.8640,test_loss:1.2788,test_acc:63.9300,test_top5_acc:89.4800\n",
      "epoch:16,train_loss:0.7394,train_acc:77.3700,train_top5_acc:96.3580,test_loss:1.2981,test_acc:64.5400,test_top5_acc:89.6300\n",
      "epoch:17,train_loss:0.6998,train_acc:78.6340,train_top5_acc:96.7640,test_loss:1.3674,test_acc:64.1200,test_top5_acc:88.6200\n",
      "epoch:18,train_loss:0.6535,train_acc:79.8440,train_top5_acc:97.1500,test_loss:1.3753,test_acc:64.0900,test_top5_acc:88.8400\n",
      "epoch:19,train_loss:0.6172,train_acc:80.9500,train_top5_acc:97.5380,test_loss:1.3663,test_acc:64.0300,test_top5_acc:88.8200\n",
      "epoch:20,train_loss:0.5813,train_acc:82.1940,train_top5_acc:97.6240,test_loss:1.3454,test_acc:64.7800,test_top5_acc:89.2400\n",
      "epoch:21,train_loss:0.5420,train_acc:83.3760,train_top5_acc:98.0960,test_loss:1.4247,test_acc:63.7000,test_top5_acc:88.5100\n",
      "epoch:22,train_loss:0.5208,train_acc:83.8100,train_top5_acc:98.2820,test_loss:1.3518,test_acc:65.1700,test_top5_acc:89.3500\n",
      "epoch:23,train_loss:0.4846,train_acc:85.0460,train_top5_acc:98.5260,test_loss:1.3200,test_acc:65.7600,test_top5_acc:89.6000\n",
      "epoch:24,train_loss:0.4473,train_acc:86.2100,train_top5_acc:98.8020,test_loss:1.2661,test_acc:67.3000,test_top5_acc:90.7100\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_losses, test_losses = [], []\n",
    "train_accs, test_accs = [], []\n",
    "train_top5_accs, test_top5_accs = [], []\n",
    "for epoch in range(epochs):\n",
    "    train_loss,train_acc,train_top5_acc=train(model,trainloader,criterion,optimizer,device)\n",
    "    test_loss,test_acc,test_top5_acc=test(model,testloader,criterion,device)\n",
    "    print('epoch:{},train_loss:{:.4f},train_acc:{:.4f},train_top5_acc:{:.4f},test_loss:{:.4f},test_acc:{:.4f},test_top5_acc:{:.4f}'.format(epoch,train_loss,train_acc,train_top5_acc,test_loss,test_acc,test_top5_acc))\n",
    "\n",
    "    train_losses.append(train_loss)\n",
    "    test_losses.append(test_loss)\n",
    "    train_accs.append(train_acc)\n",
    "    test_accs.append(test_acc)\n",
    "    train_top5_accs.append(train_top5_acc)\n",
    "    test_top5_accs.append(test_top5_acc)\n",
    "\n",
    "#画图\n",
    "torch.save(model.state_dict(), model_name+'.pth')\n",
    "plot_training_results(train_losses, train_accs, train_accs, test_losses, test_accs, test_top5_accs)\n",
    "save_log(model_name,train_accs,test_accs,train_losses,test_losses,train_top5_accs,test_top5_accs,output_dir='../train_process')"
   ]
  }
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